Nomograms Combining Clinical and Imaging Parameters to Predict Recurrence and Disease-free Survival After Concurrent Chemoradiotherapy in Patients With Locally Advanced Cervical Cancer

被引:19
作者
Zhang, Yu [1 ]
Liu, Long [2 ]
Zhang, Kaiyue [1 ]
Su, Rixin [1 ]
Jia, Haodong [1 ,3 ]
Qian, Liting [1 ]
Dong, Jiangning [1 ,3 ]
机构
[1] Anhui Med Univ, Anhui Prov Hosp, Dept Radiat Oncol, Hefei 230001, Anhui, Peoples R China
[2] Zhejiang Univ, Dept Hepatobiliary Surg, Taizhou Hosp, Taizhou, Zhejiang, Peoples R China
[3] Univ Sci & Technol China, Dept Radiol, Affiliated Hosp 1, Hefei, Anhui, Peoples R China
关键词
Cervical cancer; Concurrent chemoradiotherapy; Nomogram; Radiomics; Recurrence; Disease-free survival; INTRAVOXEL INCOHERENT MOTION; CARCINOMA; RISK; MRI;
D O I
10.1016/j.acra.2022.08.002
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Purposes: To investigate the value of nomograms based on clinical prognostic factors (CPF), intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI) and MRI-derived radiomics in predicting recurrence and disease-free survival (DFS) after concurrent chemo-radiotherapy (CCRT) for locally advanced cervical cancer (LACC).Methods: Retrospective analysis of data from 115 patients with IB-IVA cervical cancer who underwent CCRT and had been followed up consistently. All patients were randomized 2:1 into training and validation groups. Pre-treatment IVIM-DWI parameters (ADC-value, D -value, D*-value and f-value) and pre-and post-treatment three-dimensional radiomics parameters (from axial T2WI) of primary lesions were measured. The LASSO algorithm and Logistic regression analysis were used to filter texture features and calculate radiomics score (Rad-score). Multivariate Logistic and Cox regression analysis was used to construct nomograms to predict recurrence and DFS for patients with LACC after CCRT respectively, with internal and external validation.Results: External beam radiotherapy dose, f-value, pre-treatment and post-treatment Rad-score were independent prognostic factors for recurrence and DFS in patients with cervical cancer, forming Model1 and Model2, with OR values of 0.480, 1.318, 3.071, 3.200 and HR values of 0.322, 3.372, 5.138, 7.204. The area under the curve (AUC) of Model1 for predicting recurrence of cervical cancer was 0.977, with internal and external validation C-indexes of 0.977 and 0.962. The AUC for Model2 predicting disease-free survival (DFS) at 1, 3, and 5 years was 0.895, 0.888 and 0.916 respectively, with internal and external C-indexes of 0.860 and 0.892. The decision curves analysis and clinical impact curves further indicate the high predictive efficiency and stability of nomograms.Conclusion: The nomograms based on clinical, IVIM-DWI and radiomics parameters have high clinical value in predicting recurrence and DFS of patients with LACC after CCRT and can provide a reference for prognostic assessment and individualized treatment of cervical cancer patients.
引用
收藏
页码:499 / 508
页数:10
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